Impact of Globalization on Income Inequality in Selected ...gini coefficient. The study concluded that the increase in regional economic integration among European countries raise

Munich Personal RePEc Archive

Impact of Globalization on Income

Inequality in Selected Asian Countries

Bukhari, Mahnoor and Munir, Kashif

University of Central Punjab

9 September 2016

Online at https://mpra.ub.uni-muenchen.de/74248/

MPRA Paper No. 74248, posted 06 Oct 2016 14:53 UTC

Impact of Globalization on Income Inequality in

Selected Asian Countries

Mahnoor Bukhari*

&

Kashif Munir†

University of Central Punjab,

Lahore, Pakistan

* Department of Economics, University of Central Punjab, Lahore, Pakistan † Associate Professor, Department of Economics, University of Central Punjab, Lahore, Pakistan. Phone: +92 321 5136276, Fax: +92 42 35954892, email: [email protected], [email protected]

Abstract

The primary objective of this study is to investigate the relationship between globalization and

income inequality in selected Asian economies i.e. Bangladesh, China, India, Indonesia,

Malaysia, Pakistan, Philippines, Sri Lanka, Singapore, South Korea and Thailand. The specific

objectives of this study are to analyze the relationship between trade globalization, financial

globalization and technological globalization on income inequality. For attaining these objectives

this study used panel data for selected Asian countries from 1980 to 2014 for trade and

technological globalization model and from 1990 to 2014 for financial globalization model. The

study used pooled OLS and instrumental variable least square technique for estimation. Results

show that trade and technological globalization in the selected Asian economies significantly

contributes to reduce income inequality while financial globalization increase income inequality.

Education has inverse impact on income inequality while foreign direct investment has positive

relationship with income inequality. Therefore, the study suggest that government should

promote education, invest in research and development activities, establish efficient financial

system, reduce trade restrictions and provide subsidies that help to increase the volume of trade.

Keywords: Trade, Financial, Technological Globalization, Income Inequality, Panel Data, Asia

JEL: C23, F62, O53

1

1. Introduction

Globalization has made the globe more equal. As the communication around the world become

cheaper and transportation gets faster, developing countries have a chance to reduce the gap with

the rich countries. But story is opposite in many developing countries which experiences an

extremely high level of income inequality (World Economic and Social Survey 2013). The

relationship between globalization and income inequality is a subject of considerable controversy

in economic literature. On one hand globalization is considered to promote economic growth and

social welfare of the society, where developing countries have a chance to reduce the gap with

the world economy, while on the other; globalization is blamed for increasing income inequality

and environmental degradation. Globalization is considered to be a multidimensional

phenomenon, which include different aspects of political, social, cultural and economic sphere

but the major concern of economists and policy makers is economic globalization and its impact

on the income of the people (Ogunyomi et al., 2007). Economic globalization is a process of

rapid increase in the liberalization of international trade, investment, finance, and technological

changes among countries (Torres, 2001). The impact of globalization is not evenly distributed

among all segments of the society, especially the effect of globalization on employment and

income. It is widely accepted that increase in globalization is associated with rising income

inequality in the world. A combined income of 500 richest individuals in the world are greater

than 2.5 billion poor people (Watkins et al., 2005). Therefore, understanding the nature of, and

linkages between income inequality and globalization is crucial.

Globalization has been perceived by both anti-globalist commentators and pro-globalist

commentators. The anti-globalist commentators (Stiglitz, 2003) argued that globalization has

adverse effects on particularly poor economies due to the increase in within or between countries

income inequality and there is a need for government intervention to control the adverse effect of

globalization on income. While the pro-globalist commentators (Roud and Whalley, 2004;

Bhagwati, 2004) argued that increase in income inequality due to globalization is a reasonable

price to pay for the benefits of world integration and generally it leads to reduce poverty and

creating employment. Therefore, there are challenges that whether globalization lead towards

rising income inequality or dampening income inequality.

2

The world merchandise trade increased 7 percent per year on average attaining a peak of US$ 18

trillion in 2011 during the last 30 year. During this period, developing countries especially Asian

economies have seemed to play an increasing role in world trade (World Trade Report 2013). In

this globalized world, when exports benefit a bigger share of population in a country, it cause a

reduction in country’s income inequality otherwise increasing exports cause income inequality to

rise. The impact of financial globalization is associated with higher economic growth. Financial

globalization cause reduction in income inequality because of an increasing access of finance.

But this depend upon the quality of institutions in the economies. When countries have poor

quality of institutions, the advantages of financial integration are mostly accrued by rich, who

have better access to the opportunities. In case of good institutions the benefits of financial

integration are distributed among all segments of the society equally (Lee, 2014). Technological

globalization also plays an important role in the development of the economies and effects the

distribution of income, particularly for developing countries (Liu and Lawell, 2015).

There are relatively limited studies on the impact of globalization on income inequality in

advanced and developing economies. The literature on globalization (as international trade) and

income inequality is divided into two strands. The first strand advocates that due to the increase

in trade globalization there is a rise in income inequality (Silva and Leichenko, 2004; Rudra,

2004; Felbermayr, 2005; Beckfield, 2006; Ali and Isse, 2007; Meschi and Vivarelli, 2007;

Aradhyula et al., 2007; Lu and Cai, 2011; Bensidoun et al., 2011; Cassette et al., 2012; Demir et

al., 2012; Rodriguez-Pose, 2012; Munir et al., 2013; Hepenstrick and Tarasov, 2015). The second

group advocates that due to the increase in trade globalization there is a decline in income

inequality (Chakrabarti, 2000; Silva, 2007; Babones and Zhang, 2008; Tian et al., 2008;

Georgantopoulos and Tsamis, 2011). Existing literature take international trade as globalization

and measure its impact on income inequality, while only few studies take other aspects of

globalization combined with international trade. However, there exist limited work for financial

globalization and technological globalization and their effect on income inequality. The present

study aims at filling this gap by adding both financial and technological globalization combine

with trade globalization and measure its impact on income inequality.

The objective of the study is to analyze the impact of globalization on income inequality in

selected Asian economies. The study has following specific objectives: to analyze the

relationship between trade globalization and income inequality, to analyze the relationship

3

between financial globalization and income inequality, to analyze the relationship between

technological globalization and income inequality. This study will provide useful guidelines to

the policy makers and government to make effective policies in relation to globalization and

income inequality that lead towards economic growth and reducing income inequality. The

existing literature focused mostly on the one aspect of globalization (i.e. international trade) but

this study contributes to the existing literature by examining three different aspects of

globalization (i.e. trade globalization, financial globalization and technological globalization)

through which income inequality is affecting Asian economies.

The structure of the paper is as follow: Section 2 of this study provides literature on trade,

financial and technological globalization and their relationship with income inequality. Model,

methodology and data are discussed in section 3. The empirical results of trade, financial and

technological globalization on income inequality are analyzed in section 4. Conclusions and

policy recommendations are discussed in section 5.

2. Literature Review

Theoretically and empirically globalization play an important role in the development of the

countries. There are several dimensions on the relationship between globalization and income

inequality that has been investigated by researchers.

2.1. Literature on trade globalization and income inequality:

The literature on trade globalization and its relationship with income inequality is a matter of

controversies among researcher. On one hand trade globalization increase income inequality

while on the other it reduce income inequality. Therefore, the literature on trade globalization is

further divided into two sub section. The first sub section discuss a positive impact of trade on

income inequality whereas the other sub section discuss a negative literature on the relationship

between trade and income inequality.

2.1.1. The positive impact of trade globalization on income inequality

Silva and Leichenko (2004) examined the impact of foreign trade on income inequality in

different states of U.S. The study used Panel data from 1972 to 1994 by using OLS for

estimation. The results of the study suggested that expensive imports and cheaper exports

worsening the condition of income inequality in different states of United Nations. They

4

concluded that the level of inequality across and within U.S. states increased during the time

period from 1992 to 1994. Rudra (2004) investigated the relationship between government social

expenditures, openness, and income distribution among more developed and less developed

countries. Panel data consists of thirty-five less developed and eleven OECD economies from

1972 to 1996 were used by utilizing fixed effect and two stage least square estimation methods.

Results showed that trade worsened inequality only in LDC and social spending reduce

inequality only in OECD nations but spending on education also reduced inequality in LDC.

Study concluded that social expenditure condition and trade for developed economies are much

better than the less developed economies. Felbermayr (2005) revisited the association between

economies openness and per capita income. Study used panel data and the time dimension

comprised of five-year average. The first period used was 1960 to 1964 and the last period was

1995 to 1999 for 93 countries by utilizing system-GMM approach. Study found a positive trade-

income relationship and found no evidence that trade reduces income inequality. Thus he

concluded that poor and rich economies have different impact on free trade.

Beckfield (2006) investigated the relationship between national income inequality and regional

integration. Unbalanced panel data for 12 European countries from 1973 to 1997 were used.

Study employed generalized least squares, fixed and random effects methodologies. Results

showed that in all the three estimation techniques economic integration positively related with

gini coefficient. The study concluded that the increase in regional economic integration among

European countries raise income inequality. Ali and Isse (2007) investigated the effect of foreign

aid and trade openness on income distribution. Study used panel data for 150 countries from

1975 to 2000. The study used simultaneous equations system and utilized the methodology of

three-stage least squares. Results indicated that there exist positive and significant association

between international trade and GDP per worker while government spending and foreign direct

investment negatively affect income. They concluded that trade and foreign aid are solid

determinants of gdp per capita and international trade appears complementary to economic

performance. Meschi and Vivarelli (2007) analyzed the association between international trade

and within-country income inequality. Panel data from 1980 to 1999 for 65 developing countries

were used by utilizing Least Square Dummy Variable Estimation technique. Study found that the

trade openness with the industrialized economies worsen the distribution of income, whereas the

same flow towards developing economies equalize the distribution of income.

5

Aradhyula et al. (2007) analyzed the impact of openness of trade on per capita income, and

income inequality. Study used balanced and unbalanced panel data for 60 developing and

developed economies from 1985 to 1994 by using two-stage least square for estimation. Results

found that trade increases income for balanced panel. For unbalance panel trade increases

income inequality only in developing economies. Study concluded that although trade increases

inequality but its magnitude is less in developed countries. Lu and Cai (2011) examined the

relationship among trade openness, factor endowment and individual income distribution. Study

used panel data of twenty four provinces of China from 1997 to 2005 by using random and fixed

effect technique for estimation. They found that the distribution of income is equal in the land

and capital intensive provinces while the distribution of income is less equal in human capital

and labor-intensive provinces. They concluded that, overall trade openness contributes to

increase income inequality in china. Bensidoun et al. (2011) reassessed the relationship between

income distribution and international trade by taking each country specific trade pattern. The

study utilized the sample of 41 countries for the years 1970, 1980 and 1990 by using fairly

general model and different robustness test. The results of the study showed that changes in the

nature of trade has a significant impact on income distribution and its magnitude depend upon

the national income level of the country. The study concluded that international trade

significantly contributes to increase income inequalities in developing economies.

Demir et al. (2012) examined the association between trade structure, sectoral employment and

income inequality in the developing economies. Unbalanced panel data of fifty five developing

countries from 1981 to 2005 were utilized by employing IV-GMM and two-stages least square

(2SLS) for estimation. Results of the study showed that trade structure and employment are

significantly positive suggesting that rise in the share of manufactures exports and industrial

employment increase income inequality. The study concluded that different trade structure

significantly increase income inequality. Cassette et al. (2012) distinguished short run and long

run impact of international trade in goods and in services on income inequalities. The study used

annual panel data set for 10 advanced countries over 26 years from 1980 to 2005 through the use

of panel cointegration, error correction mechanism and dynamic ordinary least square estimation.

The results of the study found that trade of services has only short run impact while trade of

goods have both short and long run effect on income inequalities. The study concluded that

overall international trade cause an increase in income inequality. Rodriguez-Pose (2012)

6

investigated the association between trade openness and within country inequality. The study

used unbalanced panel data for 28 countries from 1975 to 2005 by utilizing the methodology of

both static (OLS) and dynamic (GMM) panel data analysis. Results found that rise in

international openness has a positive impact on regional inequalities. However the study

concluded that in middle and low income economies, changes in trade agreement have more

effect on income inequality than the high income countries.

Munir et al. (2013) investigated the association between trade openness and income inequality

for Pakistan. They used Cointegration Approach and vector error correction mechanism for the

period 1972 to 2008. Results found that trade, remittances, interest rate and urbanization

increases inequalities while FDI reduced it. They concluded that after liberalization, income

inequality rise in the economy of Pakistan. Hepenstrick and Tarasov (2015) investigated how

variations in trade openness contribute to cross-country income differences. The study calibrated

the model for the year 2003 for 86 countries by using OLS and the Poisson pseudo maximum

likelihood (PPML) for estimation. The study found that if the countries are full symmetric there

would be no inequality due to trade openness. But for the counterfactual world where the

countries are differ in endowment, population size and variable trade cost then income inequality

would increase due to trade.

2.1.2 The negative effect of trade globalization on income inequality

Chakrabarti (2000) explored the impact of intra-national distribution of income and international

trade. Study used data of low-income, lower middle-income, higher middle-income and high-

income countries with the total of 73 countries for the year 1985. Study employed OLS and IV

for estimation. The finding of the study showed that income inequality reduces by greater

participation in international trade and growth which offers a channel through which

international trade reduce the distribution of income inequality. Silva (2007) examined the

impact of export and domestically oriented agricultural trade on income inequality across the

developed southern region and the less developed northern regions of Mozambique. The study

used cross sectional data from 1996 to 2000 by utilizing ordinary least square. The results of the

study found that the domestic oriented agricultural trade has inequality increasing effect in

southern Mozambique. Whereas the international orientated crops export has inequality

dampening effect in northern Mozambique. Thus the study concluded that income inequality

7

varies by region and type of trade. Babones and Zhang (2008) analyzed the association between

inequality and trade by dividing countries of world into three income categories i.e., Core, Semi-

periphery and Periphery. The study used world-systems approach and estimated cross-sectional

models at five year intervals: 1980, 1985, 1990, 1995, and 2000. The results for semi peripheral

countries showed that trade are related with lower income inequality, while in core and

peripheral countries trade are related with higher income inequality. Thus the study concludes

that trade affects income inequality according to zone specific ways.

Tian et al. (2008) investigated the impact of economic globalization as FDI and international

trade on income inequality in China. Study used annual data from 1979 to 2006 by employing

ADF unit-root test and Johansen and Juselius multivariate cointegration approach. Results

showed that trade, FDI, and government spending all have a tendency to improve the condition

of income distribution. They concluded that income inequality in China are not due to the

liberalization of trade, they are caused by other factors. Georgantopoulos and Tsamis (2011)

examined the impact of globalization on income distribution in Hungary. Study utilized data

from 1990 to 2009 by employing ordinary least square. The results of the study found that the

distribution of income improve by increasing trade and foreign capital penetration, while

remittance has positive effect. The study concluded that findings follow conventional wisdom

that opening up the countries for international trade tends to reduce income inequality and

globalization process is beneficial for Hungary.

2.2. The impact of trade and financial globalization on income inequality

Spilimbergo et al. (1997) investigated the association between trade, factor endowments and the

distribution of income. Study used panel data for 34 countries from 1965 to 1992. The

methodology of Huber correction is used to calculate residuals for fixed effect model and then

performed different robustness tests. Results indicated that trade, land and education positively

affect income while the impact of financial depth were insignificant. Study concluded that in

capital abundant countries trade openness causes reduction in income inequality while in skill

abundant countries trade increase income inequality. Heshmati (2003) investigated the

association between income inequality and globalization with the help of two indices for

globalization. Panel data for 62 countries from 1995 to 2001 were utilized. Ordinary least square

technique were used for estimation. Results found that different components of globalization

8

have different effect on inequality. Technology contributes to reduce income inequality,

economic liberalization increase inequality while political engagement have no effect on income

inequality. Study concluded that developed countries have more equal distribution of income

than the developing economies. Reuveny and Li (2003) investigated the effects of democracy

and openness on the distribution of income. Study used pooled data for sixty-nine countries from

1960 to 1996 by using OLS, fixed and random effect techniques for estimation. The study

showed that democracy and trade openness reduce income inequality within countries while FDI

rise income inequality. Financial capital have no effect on the level of income distribution. Thus

the study concluded that due to economic integration income inequality decrease.

Milanovic (2005) investigate the association between openness and income distribution for poor,

rich and middle-income economies. The study used cross sectional data for ninety-five countries

for the year 1988 and 113 countries for the year 1993 by utilizing simultaneous decile and IV-

GMM for estimation. The results of the study found that trade increase inequality while financial

depth decrease it. FDI had no effect and democracy improved income inequality. The study thus

concluded that the benefits of international trade were mostly acquired by rich and the share of

income for poor are lesser in economies that are more integrated. Shahbaz et al. (2007)

investigated the association between trade-openness, financial deepening and rural-urban income

inequality. They used time series data from 1971 to 2006 for Pakistan by using modified ARDL

cointegration along with Johansson technique and ECM. Results of the study found that

improvement in financial performance reduce rural-urban income inequality, Openness in

foreign capital and trade rise rural-urban inequality and inflation is also linked with high level of

rural-urban income gap. Thus the study concluded that financial development improve inequality

while trade openness worsened it.

Ogunyomi et al. (2013) examined the impact of economic globalization and growth on income

inequality in Nigeria. They used annual time series data from the time period 1986 to 2010. The

study employed static linear model and structural simultaneous equation model. The result

showed that trade has negative impact on income inequality while financial globalization had

significantly positive effect. Thus it was concluded that due to much emphasis on financial

globalization, economic globalization tend to increase income inequality and reduce economic

growth in the Nigerian economy. Lee (2014) examined the impact of international and financial

integration on poverty and income inequality. Study used data from 1976 to 2004 for income

9

inequality model and from 1990 to 2004 for poverty model. The study used ordinary least square

as methodology. The results of the study showed that there is a conditional association between

international trade, income inequality and poverty while financial integration increases poverty

and income inequality in general.

2.3. The impact of trade, technology and financial globalization on income inequality

Jaumotte et al. (2008) examined the relationship between trade, technology and financial

globalization on income inequality. The study used data of 51 economies, out of which 20 are

advanced and 31 are developing and emerging economies and the time period was taken from

1981 to 2003. The study used ordinary least squares with heteroskedasticity-consistent standard

errors and instrumental variable least square for estimation. The results found that increased

trade tends to reduce income inequality, technological and financial globalization tends to

exacerbate it. Thus the study concluded that different modes of globalization have different

impact on income inequality. Antonelli and Gehringer (2013) examined the hypothesis that

technological changes is a major factor in the reduction of income inequalities. Study utilized the

data set of advanced and newly industrialized countries for the time period of 1995 to 2011 by

using feasible generalized least square and instrumental variable least square for estimation.

Results indicates that technology, trade, GDP per capita, investment and government expenditure

contributes to reduce inequality while financial integration increase it. Thus the study confirm

the hypothesis of inequality reducing effect of technological changes. Liu and Lawell (2015)

examined the impact of innovation measured by technological changes on income inequality in

China. Panel data on Chinese provinces over the period 1995 to 2011 were used by employing

instrumental variable least square for estimation. Results indicated that there is an inverse U-

shaped relationship between innovation and the ratio between urban and rural income. Both

industrialization and urbanization contributes to increase income inequality. Study concluded

that small amounts of innovation decrease income inequality and large amounts of innovation

increase income inequality.

The issue of globalization and its relationship with income inequality has gained much

importance in the past few years in both developed and developing countries. Policy makers also

remained interested in analyzing the relationship between them. A wide-ranging literature has

discussed the impact of globalization as international trade on income inequality in both

10

developed and developing countries. Few studies also discussed the relationship between

financial globalization and income inequality. But there are comparatively limited studies on the

impact of technological globalization on income inequality especially for Asian developing

countries.

3. Model, Methodology and Data

3.1 Model

In the 19th and early 20th century economists have started to put interest in establishing the link

between globalization and income inequality (Lindert and Williamson, 2001). The main

theoretical model that explains the relationship between north south trades is the well-known

Ricardian framework (1817), but the issue of inequality is missing in the Ricardian framework.

The effect of international trade on income inequality is explained by the Heckscher-Ohlin-

Samuelson (HOS) framework. Until the 1990s, the main theoretical model to examine the

relationship between international trade and income inequality was Hecksher-Ohlin (HO) and

Stopler-Samuelson theorem (Milanovic, 2005; and Jaumotte at al., 2008).

In HO model, there are two nations, the North (more developed) and the South (less developed)

and two factors of production. The Hecksher-Ohlin model predicts that the countries will exports

that goods whose production requires the use of their abundant and cheap factors in the

production process and import those goods whose production requires the use of their relatively

scarce and expensive factor. According to this, developing countries are expecting to import

skilled labor-intensive products and export unskilled labor –intensive products. However, the

Stolper- Samuelson theorem (1941), states that the increase in the relative price of a product

that is intensively used in the production process will increase the return of that factor, and

decrease the return of the other factor. Thus as a result, according to the HOS model, due to the

increase in trade openness (which has been rise since the 1980s), unskilled labors in the

developing countries are expected to benefit and skilled labor in developed countries are

expected to benefit from this openness. In this respect, increasing international trade is expected

to increase the income of unskilled labor in developing countries and skilled labor in developed

countries, leading to a decline in income inequality in developing countries and rise in income

inequality in developed countries.

11

Empirical studies however have cast doubts on the predictions made by the HOS model, and

pointing the existence of evidence that stand against the Stolper-Samuelson theorem

(Spilimbergo et al., 1997; Barro, 2000; and Bensidoun et al., 2011). This suggests that there is no

clear link between trade and income inequality. According to Barro (2000) rich people in

developing countries may benefit more from trade openness than the poor people because they

have better advantages of having access to the advance technologies.

Many economists have started to incorporate additional conditions into the standard HOS model

to clarify the effect of trade openness on income inequality. Meschi and Vivarelli (2009) relax

the assumption of homogenous technology between the countries in the HOS model. They argue

that due to the expansion of international trade between countries new technologies may transfer

from developed countries to developing countries, which use relatively skill intensive production

technique. Demir et al. (2012) argue that in the case of multiple factors of production there is no

direct link between HOS model and income inequality. Because HOS model based on the

assumption of only two factors of production, in the presence of more than two factors of

production, the HOS model would not make any clear cut prediction about the impact of trade

openness on income inequality. Xu (2003) modified the HOS model by adding two middle-skills

goods in the South, importable and exportable. As international trade is started in South, the two

middle-skill goods become traded with the other country, which ensure both the import

expansion (inequality-reducing effect) and export expansion (inequality-enhancing effect). Thus

the study argue that export expansion effects dominate the import expansion effects that leads to

an increase in wage inequality in the South.

Contradiction in the literature arise a question that whether the relationship between inequality

and trade globalization be understand better within a Kuznets type framework. According to

Kuznets (1955), income inequality rises until a certain income level is reached, after which

inequality begins to fall. In other words, trade liberalization probably increases average per

capita income but it may cause a much more uneven allocation of gains and losses when

distributed among different segments of the society. Dobson and Ranlogan (2009) investigated

the openness Kuznets curve for eighteen Latin American economies over the period 1982 to

2000 by utilizing instrumental variable and fixed effect methodology. The result of the study find

the presence of openness Kuznets curve and support the Kuznets hypothesis for the link between

international trade and income inequality.

12

According to Randolph and Lot (1993), income inequality is hypothesized to be a function of

linear and quadratic income terms measured in arithmetic form as: 𝑰𝑵𝑬𝑸 = 𝜶𝟎 + 𝜶𝟏𝒍𝒏𝒀+ 𝜶𝟐𝒍𝒏𝒀𝟐 + 𝝁 (1)

Where, 𝐼𝑁𝐸𝑄 is income inequality, 𝑌 is income measured by GDP per capita, 𝑌2 is square of

GDP per capita, and 𝜇 is disturbance term.

Barro (2000) include globalization variables into the above equation to check the effect of

openness on income inequality as: 𝑰𝑵𝑬𝑸 = 𝜶𝟎 + 𝜶𝟏𝒍𝒏𝒀+ 𝜶𝟐𝒍𝒏𝒀𝟐 + 𝜶𝟑𝒐𝒑𝒆𝒏𝒏𝒆𝒔𝒔+ 𝝁 (2)

The additional variable openness is measure by adding import and export as a percentage of

GDP.

3.2. Methodology

3.2.1. Econometric Model

The study has three econometric models which are based on the impact of globalization on

income inequality. All three models use income inequality as dependent variable. And a number

of explanatory variables are introduced according to the model. The first model is developed to

measure the relationship between trade globalization and income inequality. The second

econometric model is constructed to assess the relationship between financial globalization and

income inequality while the third model aimed to investigate the effect of technological

globalization on income inequality. The study used pooled OLS and IVLS estimation techniques

as methodology.

3.2.1.1. Model for Trade Globalization

The basic estimation equation for trade globalization follows the model of Randolph and Lot

(1993) and Barro (2000). The study follows Reuveny and Li (2003), Dobson and Ranlogan

(2009) and Munir et al. (2013) for incorporating additional explanatory variables i.e. FDI,

education and urban population. Thus, the econometric model for trade globalization is as

follows: 𝑮𝒊𝒕 = 𝜶𝟎 + 𝜶𝟏𝒍𝒏𝒀𝒊𝒕 + 𝜶𝟐𝒍𝒏𝒀𝒊𝒕𝟐 + 𝜶𝟑𝑻𝑶𝒊𝒕 + 𝜶𝟒𝑿𝒊𝒕 + 𝒖𝒊𝒕 (3)

13

Where, 𝐺𝑖𝑡 is gini index use to measure income inequality, 𝑌𝑖𝑡 is income measure through GDP

per capita, 𝑌𝑖𝑡2 is the square of GDP per capita, 𝑇𝑂𝑖𝑡 is trade openness, and 𝜇𝑖𝑡 is the error term. 𝑋𝑖𝑡 is a vector of control variables which includes foreign direct investment as a percentage of

GDP, education measured through enrollment in primary education and urban population as a

percentage of total population.

3.2.1.2. Model for Financial Globalization

Financial globalization is the interconnection of the world’s financial institution e.g. banking

sector, stock markets etc. Over the past two decades international financial integration has also

increased. Developed countries consider to be more financially integrated with the world, but

now developing countries have also increased their cross-border asset. It is frequently claimed

that the liberalization of global financial markets contributes to rising income inequality. The

study follows Jaumotte at el. (2008), Ogunyomi et al. (2013) and Lee (2014) for measuring the

effect of financial globalization on income inequality. Therefore, the econometric model for

financial globalization is as follows: 𝑮𝒊𝒕 = 𝜷𝟎 + 𝜷𝟏𝒍𝒏𝒀𝒊𝒕 + 𝜷𝟐𝒍𝒏𝒀𝒊𝒕𝟐 + 𝜷𝟑𝑭𝑮𝒊𝒕 + 𝜷𝟒𝑿𝒊𝒕 + 𝒖𝒊𝒕 (4)


per capita, 𝑌𝑖𝑡2 is the square of GDP per capita, 𝐹𝐺𝑖𝑡 is financial globalization, and 𝜇𝑖𝑡 is error

term. 𝑋𝑖𝑡 is a vector of control variables which includes foreign direct investment as a percentage

of GDP, education measured through enrollment in primary education and urban population as a

percentage of total population.

3.2.1.3. Model for Technological Globalization

Technological change effects income inequality through its influence on different factors of

production. If technological change increases the demand for skilled worker, than there observe a

rise in income inequality, but if technological change increases the demand for unskilled labor

this cause a reduction in income inequality. However through knowledge spill over, unskilled

labor learn from skilled labor, cause a reduction in income inequality. The estimation equation

for technological globalization follows the model of Randolph and Lot (1993). The study follows

Jaumotte at el. (2008), Antonelli and Gehringer (2013) for incorporating technological

globalization. Thus, the econometric model for technological globalization is as follows:

14

𝑮𝒊𝒕 = 𝜸𝟎 + 𝜸𝟏𝒀𝒊𝒕 + 𝜸𝟐𝒀𝒊𝒕𝟐 + 𝜸𝟑𝑻𝑮𝒊𝒕 + 𝜸𝟒𝑿𝒊𝒕 + 𝝁𝒊𝒕 (5)


per capita, 𝑌𝑖𝑡2 is the square of GDP per capita, 𝑇𝐺𝑖𝑡 is technological globalization, and 𝜇𝑖𝑡 is the

error term. 𝑋𝑖𝑡 is a vector of control variables which includes foreign direct investment as a

percentage of GDP, education measured through enrollment in primary education and urban

population as a percentage of total population.

3.2.2. Panel Data Framework

The study used panel data framework for utilizing the effect of globalization on income

inequality. Panel data has many advantages over pure time series and pure cross section data due

to its control for individual heterogeneity. Panel data provide large number of data points, large

degrees of freedom and reduce the problem of collinearity between independent variables, and

therefore improve the effectiveness of econometric estimates. The use of panel data provides a

means of reducing the magnitude of major econometric problems that often arises in empirical

studies, namely, the often heard assertion of omitted variables that correlate with explanatory

variables (Hsiao 2014). Panel data can better detect and measured effects that simply cannot be

observed in pure cross section and time series data and study the more complicated behavioral

models (Gujarati 2005). Due to these advantages the study used panel data.

The study adopted most suitable estimation technique for panel data analysis. There are several

possible ways for the estimation of panel data. The first method of estimation is pooled least

square which is used in this study because in panel framework one may assume that individual’s

observations over time are collected from different individuals so there is no serial correlation

and error terms are not heteroskedastic. The second estimation technique is fixed effect least

square dummy variable in which all variables are pooled together but each cross section has its

own intercept term. As the data of the study has the problem of omitted variable biased and

endogeneity therefore the use of fixed effect least square is not appropriates. Furthermore, fixed

effects estimator may lead a biased results due to measurement error and endogenous changes in

explanatory variables. The third estimation technique that can be used with panel data is random

effect model. This technique is not appropriate for the study because number of cross sections

are less than the number of time series. As a result, neither random effects nor fixed effects

15

estimation technique is appropriate, a more sophisticated and one of the more advanced method

like instrumental variable least square (IVLS) estimation technique is applied.

3.2.3. Instrumental Variable Least Square (IVLS)

The concept of instrumental variables was first introduced by Philip G. Wright (1928).

Instrumental variable estimation technique is used when correlation between explanatory

variables and error term is suspected. It is typically used to resolve the following problems

encountered in POLS i.e. omitted variable biased, measurement error, and endogeneity. In each

of these three cases, POLS is not able to provide consistent estimates of parameter. A general

solution of these problems are instrumental variable least square estimator, and a general practice

of that estimator, often used in the problem of endogeneity, is known as two-stage least squares

(2SLS). This technique is used as an extension of the ordinary least square method.

The study uses instrumental variable least square estimation technique as a methodology. As the

data used in the study is encountered a problem of omitted variable biased and endogeneity.

Therefore the estimation results by POLS delivers biased and inconsistent estimates. Hence the

study prefer IVLS estimation technique over POLS.

3.3. Data

The study uses data for the following Asian countries i.e. Bangladesh, China, India, Indonesia,

Malaysia, Pakistan, Philippines, Sri Lanka, Singapore, South Korea and Thailand from 1980 to

2014 for trade and technological globalization model and from 1990 to 2014 for financial

globalization model. Due to the unavailability of data for all Asian countries the study focuses on

only eleven countries. The main sources of data are “World Development Indicators”, published

by the World Bank, “International Financial Statistics Yearbook” published by International

Monetary Fund, World Income Inequality Databases (WIID), World Trade Integration and

Pakistan Economic Survey. The detailed description of variables and their sources are given in

Appendix A.

4. Results

4.1. The Impact of Trade Globalization on Income Inequality

The empirical analysis of the study starts with exploring the impact of trade globalization on

income inequality in the selected Asian economies. The study used Pooled Least Square (POLS)

16

and Instrumental Variable Least Square (IVLS) techniques for estimation. The results of POLS

in which the dependent variable is income inequality while explanatory variables are log of GDP

per capita and its square term, trade, education and foreign direct investment is presented in table

4.1.

The results of pooled least square show that the coefficient of GDP per capita is positive and

significant while its square term show negative and significant relationship with income

inequality indicates the presence of Kuznets hypothesis. The estimated coefficient of trade and

foreign direct investment indicates the existence of significant and positive impact on income

inequality. Education has negative and insignificant impact on income inequality. For checking

the reliability of the estimation results by POLS the study applied the Ramsey’s regression

specification error test (RESET) for omitted variables. The results of Ramsey test reject the null

hypothesis that there is no omitted variable in the model suggesting that model is not correctly

specified. Therefore, POLS would yield biased and inconsistent estimation results that are not

reliable. Due to the problem of omitted variable biasedness and endogeneity IVLS estimation

technique is applied. The study applied Wu-Hausman test for endogeneity. The result of Wu-

Hausman test accepting the null hypothesis that the variables are exogenous. This suggests that

IVLS remove the problem of endogeneity and omitted variable biased by instrumenting the

variables. Therefore the study preferring the results of IVLS estimation technique over POLS.

The instrumental variables used in IVLS estimation technique for removing the problem of

endogeneity are log of GDP per capita and its square term, trade, education, foreign direct

investment and urban population. The estimation results of IVLS, Ramsey’s RESET and Wu-

Hasman test are also presented in table 4.1.

The estimation results of IVLS show that the coefficients of GDP per capita and its square value

are both significant while GDP per capita shows a positive and its square term shows negative

relationship with income inequality. This indicates the existence of Kuznets inverted-U

hypothesis means income inequality first increases and after attaining a certain level its starts

decreasing. This inverted-U hypothesis is also found by Dobson and Ramlogan (2009) and

Reuveny and Li (2003).

The effect of trade openness on income inequality is negative and significant at the 5% level of

significance. This indicates that greater participation in international trade significantly

17

contributes to reduce income inequality. This inverse relationship are in favorable arguments

with trade openness. As the study focused on the analysis of the developing countries of Asia

which are generally abundant in labor intensive production. So according to the HOS framework

(1981) international trade is expected to increase the income of unskilled labor, leading to a

decline in income inequality in developing countries. The finding of this study support the HOS

framework. The result reveals that income inequality decrease under integration of countries and

economies, it is not trade globalization that is responsible for inequality, inequality can be a

result of poor infrastructure, week institutions, bad governance and unbalanced taxes and

redistribution policies. The inverse and significant effect of trade globalization on income

inequality is also found by Chakrabarti (2000), Bhatta (2002), Reuveny and Li (2003), Milanovic

(2005), Tian et al. (2008), Jaumotte et al. (2008), Georgantopoulos and Tsamis (2011) and

Ogunyomi et al. (2013).

Table 4.1: Impact of trade globalization on income inequality

Dependent Variable: Income Inequality

Independent Variables Pooled Least Square

(POLS)

Instrumental Variable

Least Square

(IVLS)

Constant -48.43446***

(7.506391) -11.33286***

(5.722955)

Ln GDP per capita 21.62380*** (1.971578)

12.33538*** (1.525353)

(Ln GDP per capita)2

-1.363238*** (0.127981)

-0.692101*** (0.100046)

Trade Openness 0.030359*** (0.005869)

-0.015912** (0.007691)

Education -0.008215 (0.006714)

-0.072276*** (0.020108)

Foreign Direct Investment 0.386453*** (0.119958)

0.228474*** (0.081665)

R-squared 0.560027 0.832712

Ramsey RESET

Misspecification Test

18.22 [0.0000]

-------

Wu-Hausman Test

-------

0.633646 [0.4266]

Note: Standard error is reported in parenthesis “( )”. ***, ** and * represents 1%, 5% and 10%

significance level respectively. The probability values are in brackets “[ ]”.

Education has inverse and significant impact on income inequality. As more people are educated

this will contributes towards reducing the gap between rich and poor in selected Asian

economies. But attaining education is expensive for the poor people. In broad-spectrum, the

18

education spending for poor people decreases because they have more children than the rich, all

this confirms a vicious circle. Therefore income inequality persists in the developing countries

due to low rate of education. The negative and significant relationship between education and

income inequality is also supported by Rudra (2004), Lee (2014), Demir et al. (2012), Cassette et

al. (2012), Meschi and Vivarelli (2009) and Jaumotte et al. (2008).

The estimated impact of foreign direct investment on income inequality indicates the existence

of positive and significant relationship. This result suggests that FDI mostly benefiting those who

are relatively higher skill intensive sector, and increasing the demand for and income of high

skilled workers. Therefore FDI contributes toward increasing income inequality in the selected

Asian economies. Tian et al. (2008), Reuveny and Li (2003), Cassette et al. (2012) and Jaumotte

et al. (2008) also find similar impact of FDI on income inequality.

4.2. The Impact of Financial Globalization on Income Inequality

The study further investigates the relationship between financial globalization and income

inequality for selected Asian countries. The results of pooled OLS is reported in table 4.2 in

which the dependent variable is Income inequality while the explanatory variables are log of

GDP per capita and its square term, financial globalization and education. The results of POLS

show that the coefficient of GDP per capita is positive and statistically significant while its

square term has negative and significant impact on income inequality. The estimated coefficient

of financial globalization and education has positive and significant relationship with income

inequality. For checking the problem of misspecification the study applied the Ramsey’s

regression specification error test (RESET) for omitted variables. The results of Ramsey test

reject the null hypothesis that there is no omitted variable in the model suggesting that model is

not correctly specified. Therefore, POLS would yield biased and inconsistent estimation results

that are not reliable. Due to the problem of omitted variable biasedness and endogeneity IVLS

estimation technique is applied. The study applied Wu-Hausman test for endogeneity. The result

of Wu-Hausman test accepting the null hypothesis that the variables are exogenous. This

suggests that the IVLS remove the problem of endogeneity and omitted variable biased by

instrumenting the variables. Therefore the study preferring the results of IVLS estimation

technique over POLS.

19


endogeneity are log of GDP per capita and its square term, education, foreign direct investment

and urban population. The estimation results of IVLS, Ramsey’s RESET and Wu-Hasman test

are also presented in table 4.2.

Table 4.2: Impact of financial globalization on income inequality



(POLS)


Least Square

(IVLS)

Constant -81.54494***

(12.59356) -46.23378***

(17.11751)

Ln GDP per capita 27.00107*** (3.079436)

18.71668*** (3.972958)


-1.531754*** (0.189254)

-1.064713*** (0.255378)

Financial Globalization 0.037169*** (0.005453)

0.042193** (0.018913)

Education 0.015225* (0.008351)

-0.010903 (0.031239)

R-squared 0.451402 0.880822

Ramsey RESET


11.55 [0.0000]

------

Wu-Hausman Test

------

1.52774 [0.2178]



The results of IVLS show that the estimated coefficients of GDP per capita and its square term

are also statistically significant in financial globalization model while GDP per capita shows a

positive and its square term shows negative relationship with income inequality. This indicates

that there exist a Kuznets inverted-U hypothesis in the selected Asian economies means income

inequality first increases and after attaining a certain level its starts decreasing. This inverted-U

hypothesis is also found by Dobson and Ramlogan (2009) and Reuveny and Li (2003).

The effect of financial globalization on income inequality is positive and statistically significant

at 5% level of significance. The result suggest that financial globalization is likely to increase

income inequality. Even though financial globalization contributes to reduce income inequality

through the increasing access of finance for the poor, but the study analyze the developing Asian

countries where the quality of institutions is week, so that the benefit of financial integration may

not be equally distributed between the rich and the poor. Mostly international corporations and

20

high income individuals have access to financial markets, so that the rich people take the

advantage of financial globalization to increase their income further. Thus financial globalization

lead to financial instability in the selected Asian economies. The significant and positive impact

of financial globalization with income inequality is also found by the empirical analysis of

Jaumotte et al. (2008), Ogunyomi et al. (2013) and Lee (2014).

Education has inverse and insignificant impact on income inequality in the financial

globalization model. Meschi and Vivarelli (2009), Demir at al. (2012) and Lee (2014) also

studied the impact of education on income inequality.

4.3. The Impact of Technological Globalization on Income Inequality

The study finally analyze the relationship between technological globalization and income

inequality in the selected Asian economies. The estimation results of pooled OLS is presented in

table 4.3 in which the dependent variable is income inequality while the explanatory variables

are log of GDP per capita and its square, technological globalization, education and foreign

direct investment. The results of POLS show that the coefficient of GDP per capita has positive

and significant relationship with income inequality while its square term also has significant but

negative impact on income inequality. The estimated coefficient of technological globalization

and education has negative and significant relationship with income inequality. Foreign direct

investment has significant and positive impact on income inequality. For checking the problem

of misspecification the study applied the Ramsey’s regression specification error test (RESET)

for omitted variables. The results of Ramsey test reject the null hypothesis that there is no

omitted variable in the model suggesting that model is not correctly specified. Therefore, POLS

would yield biased and inconsistent estimation results that are not reliable. Due to the problem of

omitted variable biasedness and endogeneity IVLS estimation technique is applied. The study

applied Wu-Hausman test for endogeneity. The result of Wu-Hausman test is insignificant

accepting the null hypothesis that the variables are exogenous. This suggests that IVLS remove

the problem of endogeneity and omitted variable biased by instrumenting the variables.

Therefore the study preferring the results of IVLS estimation technique over POLS.


endogeneity are log of GDP per capita and its square term, technology, education, foreign direct

21

investment and urban population. The estimation results of IVLS, Ramsey’s RESET and Wu-

Hasman test are also reported in table 4.3.

Table 4.3: Impact of technological globalization on income inequality



(POLS)


Least Square

(IVLS)

Constant -39.95911***

(7.926956) -8.293146***

(7.868079)

Ln GDP per capita 17.95872*** (2.207090)

11.21712*** (1.943509)


-0.953871*** (0.160006)

-0.623352*** (0.120028)

Technological Globalization -0.189946***

(0.043527) -0.034935* (0.018380)

Education -0.015209** (0.006457)

-0.058286*** (0.019393)

Foreign direct Investment 0.659854*** (0.091628)

0.191326*** (0.056411)

R-squared 0.550219 0.881951

Ramsey RESET


7.82 [0.0000]

------

Wu-Hausman Test ------ 0.541351 [0.4624]



The results of IVLS show that the estimated coefficients of GDP per capita has significant and

positive relationship with income inequality while its square term has negative and significant

effect on income inequality. This indicates that there exist a Kuznets inverted-U hypothesis

between gross domestic products per capita and income inequality means income inequality first

increases and after attaining a certain level its starts decreasing. This inverted-U hypothesis is

also found by Dobson and Ramlogan (2009) and Reuveny and Li (2003).

The estimated impact of technological globalization on income inequality shows inverse and

statistically significant relationship. The result of the study find the evidence of income

inequality reducing effect with technological globalization. Technological globalization is a

force of creative destruction generally leads to create new jobs and industries. Although this

technological globalization increase the demand of high skilled labor but there is a knowledge

spillovers among the workers. As knowledge spillovers allow the fewer skills workers to learn

from the highly skilled workers, and to increase their productivity. All this cause a decrease in

22

income inequality because through knowledge rich environment due to technological

globalization, the low skilled workers learn and gain from this globalization. Technological

globalization magnifies the rates of economic growth and hence increase the income levels

employing a reduction in income inequality. Thus technological globalization contributes to

reduce income inequality in the selected Asian countries. The result of negative and significant

impact of income inequality and technological globalization is also found by Antonelli and

Gehringer (2013), Heshmati (2003) and Liu and Lawell (2015).

Result shows that the impact of education on income inequality is negative and significant

reducing the gap between rich and poor. As the study analyze the developing countries of Asia,

where acquiring education is difficult for poor people, because poor people have more children

than the rich. Therefore, the poor remain less educated and have less employment opportunities

than the rich, so income inequality persists. Rudra (2004), Lee (2014), Demir et al. (2012),

Cassette et al. (2012), Meschi and Vivarelli (2009) and Jaumotte et al. (2008) also found the

inverse and significant impact of education and income inequality.

Foreign direct investment and income inequality indicates the existence of positive and

significant relationship. This result suggests that FDI contribute towards increasing income

inequality and mostly benefiting the high skill workers. The impact of positive and significant

relationship between FDI and income inequality is also found by Tian et al. (2008), Reuveny and

li (2003), Cassette et al. (2012) and Jaumotte et al. (2008).

5. Conclusion

The goal of this study is to examine the impact of three modes of globalization separately on

income inequality. These three mode includes trade globalization, financial globalization and

technological globalization. The time period for data analysis is from 1980 to 2014 for trade and

technological globalization model and from 1990 to 2014 for financial globalization model. The

study includes eleven Asian countries and data collected at an annual frequency. The study has

excluded other Asian countries from the analysis due to data limitations.

The study used Hecksher-Ohlin and the Stolper-Samuelson theorem as a theoretical model for

the relationship between globalization and income inequality. This study follows the model of

Randolph and Lot (1993) and then augment it for incorporating globalization variable into the

model (Barro, 2000). The study further incorporates some control variables into the model i.e.,

23

enrollment in primary education, foreign direct investment and urban population. This study used

panel data framework because panel data reduce the magnitude of major econometric problems

that arises in pure time series and cross section data. This study used pooled least square and

instrumental variable least square estimation technique but prefers the results of IVLS over

POLS because in the estimation results by POLS there exist problems of omitted variable biased

and endogeneity.

Results indicates that trade significantly contributes to reduce income inequality in the selected

Asian economies. This negative impact of trade for developing countries is consistent with the

finding of Hecksher-Ohlin and the Stolper-Samuelson theorem. This inverse relationship are in

favorable arguments with trade openness. The impact of financial globalization on income

inequality suggested that financial integration cause an increase in income inequality. Therefore

the benefits of financial globalization is not evenly distributed among the rich and the poor. The

estimated impact of technological globalization also significantly contributes in the reduction of

income inequality. As globe is integrated with the technology, people with low skills learns

through knowledge spill over by the high skills workers and then get employment, therefore

inequality in the income declines. In all three models the coefficient of GDP per capita and its

square term is significant while GDP per capita has positive and square of GDP per capita has

negative sign show the existence of Kuznets hypothesis indicating that income inequality in the

selected Asian developing countries first increase and after attaining a certain level it starts

decreasing.

The results of control variables show that enrollment in primary education has negative impact

on income inequality, as enrollment in the education increases this will contributes to reduce the

gap between rich and poor. The estimated impact of foreign direct investment suggests that FDI

mostly benefits high skill intensive sector therefore cause an increase in income inequality.

Therefore, it is concluded that the trade and technological globalization contributes in the

reduction of income inequality while financial globalization indicates the existence of greater

income inequality for the selected Asian countries.

In the light of above findings the present study suggest following policy recommendations:

• Government should reduce trade restrictions and provide subsidies that help to increase

the volume of trade and reduce income inequality.

24

• Government should invest in research and development activities to enhance

technological globalization and build institutions that trained the low skills workers

which contributes in the reduction of income inequality.

• Government should establish the advance, competitive and powerful financial system

which lead towards economic growth and decrease income inequality.

• Government take steps to promote education and provide free education at least up to the

secondary level to reduce income inequality.

25

References

Alderson, A. S., & Nielsen, F. (2002). Globalization and the Great U-Turn: Income Inequality

Trends in 16 OECD Counries. AJS, 107(5), 1244-1299.

Ali, A. M., & Isse, H. S. (2007). Foreign Aid and Free Trade and Their Effect on Income: A

Panel Analysis. The Journal of Developing Areas, 41(1), 127-142.

Antonelli, C., & Gehringer, A. (2013). Innovation and Income Inequality. Working Paper Series

24/13, 1-22.

Aradhyula, Rahman, & Seenivasan. (2007). Impact of International Trade on Income and

Income Inequality. Portland.

Babones, S., & Zhang, X. (2008). Heterogenity in the Global South in the relationship between

Income Inequality and Foreign Trade. International Review of Modern Sociology, 34(1),

95-108.

Barro, R. J. (2000). Inequality and Growth in a Panel of Countries. Journal of Economic Growth,

5, 5-32.

Beckfield, J. (2006). European Integration and Income Inequality. American Sociological

Review, 71(6), 964-985.

Bensidoun, I., Jean, S., & Sztulman, A. (2011). International trade and Income Distribution:

reconsidering the evidence. Review of World Economics / Weltwirtschaftliches Archiv,

147(4), 593-619.

Bhagwati, J. N. (2004). In Defense of Globalization. New York: Oxford University Press.

Bhatta, S. D. (2002). Has the Increase in World-Wide Openness to Trade Worsened Global

Income Inequality? Papers in Regional science, 81, 177-196.

Cassette, A., Fleury, N., & Petit, S. (2012). Income Inequalities and International Trade in Goods

and Services: Short- and Long-Run Evidence. The International Trade Journal, 26(3),

223-254.

Chakrabarti, A. (2000). Does Trade Cause Inequality? Journal of Economic Development, 25(2),

1-21.

26

Clements, B. J., & Kim, K. S. (1988). Foreign Trade and Income Distribution: The case of

Brazil. The Helen Kellogg Institute For International studies, Working Paper # 108.

Demir, F., Ju, J., & Zhou, Y. (2012). Income Inequality and Structures of International Trade.

Asia-Pacific Journal of Accounting & Economics, 19(2), 167-180.

Dobson, S., & Ramlogan, C. (2009). Is There an Openness Kuznets Curve? Kyklos, 62(2), 226-

238.

Felbermayr, G. J. (2005). Dynamic Panel Data Evidence on the Trade-Income Relation. Review

of World Economics / Weltwirtschaftliches Archiv, 141(4), 583-611.

Georgantopoulos, A. G., & Tsamis, A. D. (2011). The Impact of Globalization on Income

Distribution:The Case of Hungary. Research Journal of International Studies(21), 17-25.

Hall, J. D. (2016). The Diffusion of Technology, Education and Income Inequality: Evidence

from Developed and Developing Countries.

www.researchgate.net/publication/228419624

Hepenstrick, C., & Tarasov, A. (2015). Trade Openness and Cross-country Income Differences.

Review of International Economics, 23(2), 271-302.

Heshmati, A. (2004). The Relationship between Income Inequality, Poverty and Globalisation.

IZA, Discussion Paper No. 1277.

Hsiao, C. (2014). Analysis of Panel Data. California: Cambridge University Press.

Jaumotte, F., Lall, S., & Papageorgiou, C. (2008). Rising Income Inequality: Technology, or

Trade and Financial Globalization? IMF Working Paper 08/185. International Monetary

Fund.

Kanbur, R. (2013). Globalization and Inequality. Retrieved from

http://kanbur.dyson.cornell.edu/papers/GlobalizationAndInequality

Kim, S. Y. (2012). Technological Kuznets Curve? Technology, Income Inequality, and

Government Policy. Asian Research Policy, 3, 33-49.

Kuznets, S. (1955). Economic Growth and Income Inequality. The American Economic Review,

45(1), 1-28.

27

Lee, K.-K. (2014). Globalization, Income Inequality and Poverty: Theory and Empirics. Social

System Studies, 28, 109-134.

Lindert, P. H., & Williamson, J. G. (2001). Does Globalization Make the World More Unequal?

National Bureau of Economic Research.

Liu, Q., & Lawell, C.-Y. C. (2015). The Effects of Innovation on Income Inequality in China.

http://www.des.ucdavis.edu/faculty/Lin/China_innovation_inequality_paper.pdf

Lu, X., & Cai, G. (2011). Effective Factor Endowments, Trade Openness and Income

Distribution in China. Frontier of Economies. 6(2), 188-210.

Mahler, V. A. (2004). Economic Globalization, Domestic Politics, and Income Inequality in the

Developed Countries : A Cross-National Study. Comparative Political Studies, 37(9),

1025-1053.

Majeed, M. T. (2013). Inequality, Trade and Development: Evidence from Developing

Countries. MPRA Paper No.50337.

Meschi, E., & Vivarelli, M. (2009). Trade and Income Inequality in developing Countries. World

Development, 37(2), 287-302.

Milanovic, B. (2005). Can We Discern the Effect of Globalization on Income Distribution?

Evidence from Household Surveys. The World Bank Economic Review, 19(1), 21-44.

Munir, S., Kiani, A. K., Khan, A., & Jamal, A. (2013). The Relationship between Trade

Openness and Income Inequalities Empirical Evidences from Pakistan (1972-2008).

Academic Journal of Management Sciences, 2(1), 21-35.

Ogunyomi, O. O., Daisi, O. R., & Oluwashikemi, R. A. (2013). Economic Globalization, Income

Inequality and Economic Growth in Nigeria: A Static Data Analysis (1986-2010). ABC

Journal of Advanced Research, 2(2), 55-68.

Randolph, S. M., & Lott, W. F. (1993). Can the Kuznets Effect Be Relied on to Induce

Equalizing Growth? World Development, 21(5), 829-840.

Reuveny, R., & Li , Q. (2003). Economic Openness, Democracy and Income Inequality: An

Empirical Analysis. Comparative Political Studies, 36(5), 575-601.

28

Ricardo, D. (1817). The Principles of Political Economy and Taxation. Retrieved from

http://socserv.mcmaster.ca/econ/ugcm/3113/ricardo/principles.pdf

Rodriguez-Pose, A. (2012). Trade and Regional Inequality. Economic Geography, 88(2), 109-

136.

Round, J., & Whalley, J. (2004). Globalization and Poverty: Implications of South Asian

Experience for Wider Debate. Institute of Development studies, 35(1), 11-19.

Rudra, N. (2004). Openness, Welfare Spending, and Inequality in the Developing World.

International Studies Quarterly, 48(3), 683-709.

Shahbaz, M., Aamir, N., & Butt, M. S. (2007). Rural-Urban Income Inequality under Financial

Development and Trade Openness in Pakistan: The Econometric Evidence. The Pakistan

Development Review, 46(2), 657-672.

Silva, J. A. (2007). Trade and Income Inequality in a Less Developed Country: The Case of

Mozambique. Economic Geography, 83(2), 111-136.

Silva, J. A., & Leichenko, R. M. (2004). Regional Income Inequality and International Trade.

Economic Geography, 80(3), 261-286.

Spilimbergo, A., Landono, J. L., & Szekely, M. (1997). Income Distribution, Factor

Endowments, and Trade Openness. Journal of Development Economics, 59(1), 77-101.

Stiglitz, J. E. (2003). Globalization and Its Discontents. Economic Notes, 32(1), 123-142.

Stolper, W., & Samuelson, P. (1941). Protection and Real Wages. The Review of Economic

Studies, 9(1), 58-73.

Tian, X., Wang, B., & Dayanandan, A. (2008). The Impact of Economic Globalization on

Income Distribution: Empirical Evidence in China. Economics Bulletin, 4(35), 1-8.

Torres, R. (2001). Towards a Socially Sustainable World Economy: An analysis of the Social

Pilliars of Globalization. International Labour Office. Retrieved from

http://staging.ilo.org/public/libdoc/ilo/2001/101B09_29_engl.

Vos, R., & Geest, W. V. (2013). World Economic and Social Survey 2013. United Nations.

Retrieved from

https://sustainabledevelopment.un.org/content/documents/2843WESS2013.pdf

29

Wade, R. H. (2001). Is Globalization Making World Income Distribution More Equal? Working

Paper 01/10. London school of Economics.

Watkins, k., Fu, H., Fuentes, R., Ghosh, A., Gismberardini, C., Johansson, C., . . . Yaqub, S.

(2005). International Cooperation at a Crossroads: Aid, Trade and Security in an

Unequal World. Human Development Report . New York: United Nations Development

Programme.

World Trade Report (2013). Retrieved from https://www.wto.org/english/res_e/booksp_e/wtr13-

0_e.pdf

Wright, P. G. (1928). The Tariff on Animal and Vegetable Oils. The Macmillan Company.

Xu, B. (2003). Trade Liberalization, Wage Inequality, and Endogenously Determined Nontraded

Goods. Journal of International Economics, 60(2), 417-431.

Zhang, X., & Zhang, K. H. (2003). How does Globalization Affect Reginal Inequality within a

Developing Country? Evidence from China. The Journal of Development studies, 39(4),

47-67.

30

Appendix A

Variable Description Source

G

Gini index used to measure income inequality. For missing values of gini in the data, study applied the technique of interpolation and find missing values.

World Development Indicator (WDI) and World Income Inequality database (WIID).

Y Income measured by gross domestic product per capita (GDPpc) in US $ at current price.

World Development Indicator (WDI).

Y2 Square of income measured by the square of gross domestic product per capita (GDPpc) in US $ at current price

World Development Indicator (WDI)

TO Trade openness calculated as sum of exports and imports as a percentage of GDP.

World development Indicator (WDI) and World Trade Integration.

FG

Financial globalization calculated as a sum of foreign assets and foreign liabilities as a percentage of GDP. Where foreign assets includes: portfolio debt, portfolio equity, foreign direct investment (assets) and reserves excluding gold stocks. And foreign liabilities includes: portfolio debt, portfolio equity and foreign direct investment (liabilities).

World Development Indicator (WDI) and International Financial Statistics (IFS).

TG Technological globalization proxied by Fixed telephone subscriptions per 100 people.

World Development Indicator (WDI).

X

List of control variables includes:

• Foreign direct investment as a percentage of GDP.

• Education measured by the enrollment in primary education.

• Urban population as percentage of total population.

World Development Indicator, (WDI) and Pakistan Economic Survey.

31

Documents

Impact of Globalization on Income Inequality in Selected ...gini coefficient. The study concluded that the increase in regional economic integration among European countries raise